An agent-based model of the cognitive mechanisms underlying the origins of creative cultural evolution

Abstract

Using a computational model of cultural evolution in which neural network based agents evolve ideas for actions through invention and imitation, we tested the hypothesis that this is due to the capacity for recursive recall. We compared runs in which agents were limited to single-step actions to runs in which they used recursive recall to chain simple actions into complex ones. Chaining resulted in higher cultural diversity, open-ended generation of novelty, and no ceiling on the mean fitness of actions. Both chaining and no-chaining runs exhibited convergence on optimal actions, but without chaining this set was static while with chaining it was ever-changing. Chaining increased the ability to capitalize on the capacity for learning. These findings show that the recursive recall hypothesis provides a computationally plausible explanation of why humans alone have evolved the cultural means to transform this planet.

Innovativeness as an emergent property: a new alignment of comparative and experimental research on animal innovation

“…Some authors view the creative processes underpinning innovation in humans as fundamentally different from those involved in non-human animals. These include (i) chaining, the ability to combine simple ideas into complex ones and (ii) contextual focus, the ability to shift from a convergent to a divergent thinking when the fitness of one's current actions is low [4,5,54]. Another possibility is the intellectual capacity for ratchet evolution where the knowledge of each generation builds upon knowledge transferred from the previous generation.…”

“…Are the mechanisms and drivers of innovation and creativity comparable to those in humans? Some researchers see them as qualitatively different, with human innovations calling on the ability to chain simple ideas into more complex ideas and to shift from convergent to divergent thinking [4,5]. Perhaps humans chain ideas, whereas non-human animals remain, broadly speaking, more limited to chaining motor actions [6].…”

How to get from ‘AI Tools’ to ‘AI Selves’

“…Sure, there's no reason why not. Autocatalytic networks have inspired computer programs for both computer-generated creativity (Bell & Gabora, 2016a,b;DiPaola & Gabora, 2009;DiPaola & Gabora & McCaig, 2018;Goes et al, 2016;McCaig, DiPaola & Gabora, 2016) and models of human creativity (Gabora & DiPaola, 2012;Gabora, & Saberi, 2011;Gabora, Leijnen, Veloz, & Lipo, 2011;Gabora & Tseng, 2014, 2017Veloz, Temkin, & Gabora, 2012). These efforts, though successful, have given us glimpses into how complex an artificial RAF would have be to autonomously restructure itself through the process of 'catalyzing' meaningful new ideas from existing ones.…”